CN107036560B - The Surface Roughness Detecting Method of optical glass accurate grinding processing - Google Patents

The Surface Roughness Detecting Method of optical glass accurate grinding processing Download PDF

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CN107036560B
CN107036560B CN201610986538.3A CN201610986538A CN107036560B CN 107036560 B CN107036560 B CN 107036560B CN 201610986538 A CN201610986538 A CN 201610986538A CN 107036560 B CN107036560 B CN 107036560B
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image
formula
area
roughness
optical glass
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CN107036560A (en
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姜晨
王鹏
任鹤
张瑞
姚磊
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University of Shanghai for Science and Technology
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University of Shanghai for Science and Technology
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical means
    • G01B11/30Measuring arrangements characterised by the use of optical means for measuring roughness or irregularity of surfaces

Abstract

The present invention relates to a kind of Surface Roughness Detecting Methods of optical glass accurate grinding processing, digit optical camera is mounted on machine tooling region first, workpiece surface photo after shooting grinding, then the surface for obtaining optical glass by Digital Image Processing is crisp, moulding removes area, and removes area ratio by the surface brittleness of calculating optical glass;Last basis derives the relationship of surface roughness and optical glass surface plastic removal area ratio, the surface roughness of calculating optical glass.This method effectively simplifies the surface quality detection process in optical glass device precision machining processes, improves manufacture efficiency, reduces processing cost, improves the process flow of optical element precision manufactureing.

Description

The Surface Roughness Detecting Method of optical glass accurate grinding processing
Technical field
The present invention relates to the tables that a kind of Surface Roughness Detecting Method more particularly to a kind of optical glass accurate grinding are processed Surface roughness detection method.
Background technique
Optical glass is basis and the important component of photoelectric technology industry.Especially after the 1990s, With continuous the merging of optics and electronic information science, new material science, the optical glass as photoelectron basic material is in light Transmission, light storage and the application in the big field of photoelectric display three are even more to advance by leaps and bounds, and become social informatization especially photoelectric information One of the basic condition of technology development.Due to the extensive use of optical glass, traditional manufacturing technology is increasingly difficult to meet height Effect, high-precision manufacture need.Current optical glass device there is technical issues that surface quality detection, restrict Manufacture efficiency it is constantly improve, it is difficult to meet the requirement of modern high technology assembly technology development.For the technical bottleneck, this hair A kind of bright Surface Roughness Detecting Method for devising efficient, economic optical glass accurate grinding process.
Summary of the invention
High-efficiency and economic, which is difficult to, the present invention be directed to surface roughness when optical glass grinding measures this technical problem, It is proposed that a kind of surface roughness based on the assessment of optical glass surface brittle removal area ratio calculates method, this method passes through number Optical camera shoots workpiece surface photo, and the surface brittleness of calculating optical glass removes area ratio, to obtain in manufacturing process The surface roughness of workpiece.
The technical solution adopted by the present invention are as follows: a kind of Surface Roughness Detecting Method of optical glass accurate grinding processing, Step includes:
1) surface brittleness removal area and surface roughness relational model are established:
The pit in optical glass removal region extends to surface by transversal crack and is formed, i.e., brittle removal, lateral slight crack expand Exhibition track is exponential function:
Chi=Ke·Cli 2 (1)
Wherein:
Chi- pit depth
Cli- impression pit radius
Ke- proportionality coefficient
According to surface roughness RzDefinition:
Wherein hpeakiFor 5 peak values neighbouring in the sampled contour region of surface, hvalleyiFor in the sampled contour region of surface 5 neighbouring valleies, each pit depth are equal to the sum of adjacent peak and valley, and formula (2) are deformed and bring (1) into Formula (2), then:
The surface brittleness of sampling area removes area SBFor the area of 5 neighbouring pits, may be expressed as:
Formula (4) are substituted into formula (3), are obtained about surface roughness RzArea S is removed with material fragilityBRelationship:
2) image procossing and surface brittleness remove area ratio rBIt calculates
The first step obtains workpiece surface appearance:
With five positions of digit optical camera stochastical sampling workpiece surface, workpiece surface digital photos are obtained;
Second step, image procossing:
(1) image gray processing: the surface number color image P obtained by digit optical camera is converted into following formula Gray level image:
P1=0.299R+0.587G+0.114B (6)
Wherein: P1For gray level image, R, G, B are the red, green, blue color component of digital color image;
(2) image grayscale enhances: being equalized using histogram to gray image P1It is handled, obtains the image of grey level enhancement P2:
P2The tonal range of (x, y) is [a, b], using formula (7) by image P2The tonal range of (x, y) expand to [c, D], M is the maximum gradation value in original image:
(3) image binaryzation: binarization threshold is set as (d-c)/2, by P2In be greater than threshold value take 1, take 0 less than threshold value, To obtain the black white image P for there was only two-stage gray scale3
(4) image expansion and corrosion:
1. image expansion: using formula (8), traverse image P with the structure primary matrices A of 5 X 53Each pixel value, Image P after being expanded4:
Wherein:Φ is empty set
2. Image erosion: using formula (9), traverse image P with the structure primary matrices A of 5 X 54Each pixel value, Image P after being corroded5:
(5) it marks:
In binary picture P5In, each surface plasticity is removed into the area that the area value in region is 1 and is marked And be added, acquisition total image area inner surface plastic removal area is SD, then calculating surface brittleness removal area is Sw-SD, And then calculate surface brittleness removal area ratio rB:
Wherein: Sw- total image area;
3) proportionality coefficient is demarcated
The r of five images is calculated by above-mentioned stepsB, arithmetic mean of instantaneous value is taken, is surveyed by Portable Surface Roughometer The surface roughness R of five images outz, arithmetic mean of instantaneous value is taken, formula (10) are substituted into formula (5), obtain formula:
By resulting rBAnd RzArithmetic mean of instantaneous value substitute into formula (11), obtain KeValue;
4) surface roughness of actual processing process is calculated
It is crisp using step 2) and the resulting surface of step 3) with the workpiece surface in digit optical camera shooting process Property removal area ratio rB, digital photos sampling gross area SwAnd Proportional coefficient Ke, it is thick that workpiece surface is calculated by formula (11) Rugosity Rz
The beneficial effects of the present invention are: this method effectively simplifies the workpiece surface matter of optical glass device precision manufactureing process Testing process is measured, manufacture efficiency is improved, reduces processing cost, improves the process flow of optical element precision manufactureing.
Detailed description of the invention
Fig. 1 is the flow chart for the Surface Roughness Detecting Method that optical glass accurate grinding of the invention is processed.
Specific embodiment
The invention will be further described with embodiment with reference to the accompanying drawing.
As shown in Figure 1, a kind of Surface Roughness Detecting Method of optical glass accurate grinding processing, step include:
1) surface brittleness removal area and surface roughness relational model are established:
The pit in optical glass removal region extends to surface by transversal crack and is formed, i.e., brittle removal, lateral slight crack expand Exhibition track is exponential function:
Chi=Ke·Cli 2 (1)
Wherein:
Chi- pit depth
Cli- impression pit radius
Ke- proportionality coefficient
According to surface roughness RzDefinition:
Wherein hpeakiFor 5 peak values neighbouring in the sampled contour region of surface, hvalleyiFor in the sampled contour region of surface 5 neighbouring valleies, each pit depth are equal to the sum of adjacent peak and valley, and formula (2) are deformed and bring (1) into Formula (2), then:
The surface brittleness of sampling area removes area SBFor the area of 5 neighbouring pits, may be expressed as:
Formula (4) are substituted into formula (3), are obtained about surface roughness RzArea S is removed with material fragilityBRelationship:
2) image procossing and surface brittleness remove area ratio rBIt calculates
The first step obtains workpiece surface appearance:
With five positions of digit optical camera stochastical sampling workpiece surface, workpiece surface digital photos are obtained;
Second step, image procossing:
(1) image gray processing: the surface number color image P obtained by digit optical camera is converted into following formula Gray level image:
P1=0.299R+0.587G+0.114B (6)
Wherein: P1For gray level image, R, G, B are the red, green, blue color component of digital color image;
(2) image grayscale enhances: being equalized using histogram to gray image P1It is handled, obtains the image of grey level enhancement P2:
P2The tonal range of (x, y) is [a, b], using formula (7) by image P2The tonal range of (x, y) expand to [c, D], M is the maximum gradation value in original image:
(3) image binaryzation: binarization threshold is set as (d-c)/2, by P2In be greater than threshold value take 1, take 0 less than threshold value, To obtain the black white image P for there was only two-stage gray scale3
(4) image expansion and corrosion:
1. image expansion: using formula (8), traverse image P with the structure primary matrices A of 5 X 53Each pixel value, Image P after being expanded4:
Wherein:Φ is empty set
2. Image erosion: using formula (9), traverse image P with the structure primary matrices A of 5 X 54Each pixel value, Image P after being corroded5:
(5) it marks:
In binary picture P5In, each surface plasticity removal region (area value 1) is marked and is added, is schemed As gross area inner surface plastic removal area is SD, then calculating surface brittleness removal area is Sw-SD, and then calculate table Face brittle removal area ratio rB:
Wherein: Sw- total image area;
3) proportionality coefficient is demarcated
The r of five images is calculated by above-mentioned stepsB, arithmetic mean of instantaneous value is taken, is surveyed by Portable Surface Roughometer The surface roughness R of five images outz, arithmetic mean of instantaneous value is taken, formula (10) are substituted into formula (5), obtain formula:
By resulting rBAnd RzArithmetic mean of instantaneous value substitute into formula (11), obtain KeValue;
4) surface roughness of actual processing process is calculated
It is crisp using step 2) and the resulting surface of step 3) with the workpiece surface in digit optical camera shooting process Property removal area ratio rB, digital photos sampling gross area SwAnd Proportional coefficient Ke, it is thick that workpiece surface is calculated by formula (11) Rugosity Rz

Claims (1)

1. a kind of Surface Roughness Detecting Method of optical glass accurate grinding processing, which is characterized in that step includes:
1) surface brittleness removal area and surface roughness relational model are established:
The pit in optical glass removal region extends to surface by transversal crack and is formed, i.e., brittle removal, lateral slight crack extend rail Mark is exponential function:
Chi=Ke·Cli 2 (1)
Wherein:
Chi- pit depth
Cli- impression pit radius
Ke- proportionality coefficient
According to surface roughness RzDefinition:
Wherein hpeakiFor 5 peak values neighbouring in the sampled contour region of surface, hvalleyiIt is neighbouring in the sampled contour region of surface 5 valleies, each pit depth is equal to the sum of adjacent peak and valley, and formula (2) are deformed and (1) is brought into formula (2), then:
The surface brittleness of sampling area removes area SBFor the area of 5 neighbouring pits, may be expressed as:
Formula (4) are substituted into formula (3), are obtained about surface roughness RzArea S is removed with material fragilityBRelationship:
2) image procossing and surface brittleness remove area ratio rBIt calculates
The first step obtains workpiece surface appearance:
With five positions of digit optical camera stochastical sampling workpiece surface, workpiece surface digital photos are obtained;
Second step, image procossing:
(1) the surface number color image P obtained by digit optical camera image gray processing: is converted into gray scale with following formula Image:
P1=0.299R+0.587G+0.114B (6)
Wherein: P1For gray level image, R, G, B are the red, green, blue color component of digital color image;
(2) image grayscale enhances: being equalized using histogram to gray image P1It is handled, obtains the image P of grey level enhancement2:
P2The tonal range of (x, y) is [a, b], using formula (7) by image P2The tonal range of (x, y) is expanded to [c, d], M Maximum gradation value in original image:
(3) image binaryzation: binarization threshold is set as (d-c)/2, by P2In be greater than threshold value take 1,0 is taken less than threshold value, to obtain Must there was only the black white image P of two-stage gray scale3
(4) image expansion and corrosion:
1. image expansion: using formula (8), traverse image P with the structure primary matrices A of 5 X 53Each pixel value, obtain Image P after expansion4:
Wherein:Φ is empty set
2. Image erosion: using formula (9), traverse image P with the structure primary matrices A of 5 X 54Each pixel value, obtain Image P after corrosion5:
(5) it marks:
In binary picture P5In, each surface plasticity is removed into the area that the area value in region is 1, simultaneously phase is marked Add, acquisition total image area inner surface plastic removal area is SD, then calculating surface brittleness removal area is Sw-SD, in turn Calculate surface brittleness removal area ratio rB:
Wherein: Sw- total image area;
3) proportionality coefficient is demarcated
The r of five images is calculated by above-mentioned stepsB, arithmetic mean of instantaneous value is taken, measures five by Portable Surface Roughometer The surface roughness R of imagez, arithmetic mean of instantaneous value is taken, formula (10) are substituted into formula (5), obtain formula:
By resulting rBAnd RzArithmetic mean of instantaneous value substitute into formula (11), obtain KeValue;
4) surface roughness of actual processing process is calculated
With the workpiece surface in digit optical camera shooting process, gone using step 2) and the resulting surface brittleness of step 3) Except area ratio rB, digital photos sampling gross area SwAnd Proportional coefficient Ke, workpiece surface roughness is calculated by formula (11) Rz
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Publication number Priority date Publication date Assignee Title
CN108724002B (en) * 2018-05-31 2020-04-21 上海理工大学 Surface roughness calculation method for plane grinding workpiece
CN109015125B (en) * 2018-07-23 2020-08-25 江苏理工学院 Hard and brittle material ductility domain grinding determination method based on brittleness removal proportion coefficient and surface roughness

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